Vector Databases Explained: Design Choices and Trade-Offs

In this video, we break down how vector databases are used in real production systems, and the key design decisions you need to make when building semantic search and recommendation engines. Using a real system built at Ready Tensor as a case study, we walk through common vector database use cases, compare popular database options, and explain the practical trade-offs behind each architectural choice. You'll learn how to: * Understand the core use cases for vector databases: semantic search and recommendations * Compare popular vector DB options like PGVector, Chroma, FAISS, Milvus, and Pinecone * Choose the right database based on scale, cost, persistence, and operational control * Select embedding models with the right balance of performance, latency, and privacy * Think through embedding dimensionality and its impact on compute and memory * Apply chunking strategies and understand when they matter * Choose similarity metrics and interpret their outputs * See how vector search powers real-world applications in production Timestamps: 0:00 - Why vector databases matter in agentic AI systems 0:40 - Core use cases: semantic search and recommendations 1:17 - Choosing a vector database: key questions and trade-offs 3:55 - Embedding model decisions: open source vs APIs 6:03 - Chunking strategies and when they matter 7:34 - Similarity metrics and why cosine similarity is common 8:19 - System architecture overview 8:45 - Live demo: semantic search and recommendations in production Watch this video if you're building RAG systems, recommendation engines, or production-ready agentic AI applications and want to make informed infrastructure decisions instead of guessing. This video is part of the LLM Engineering and Deployment Certification Program by Ready Tensor. Enroll Now: https://www.readytensor.ai/agentic-ai-essentials-cert/ About Ready Tensor: Ready Tensor helps AI and ML professionals build, evaluate, and showcase real-world intelligent systems through certifica